Update app.py

Revert to InferenceClient to avoid local model loading

app.py

@@ -3,36 +3,15 @@ from huggingface_hub import InferenceClient
 import time
 import os
 import traceback
-from transformers import MBartForConditionalGeneration, MBartTokenizer
 
 HF_TOKEN = os.getenv("HF_TOKEN")
 if not HF_TOKEN:
     raise ValueError("HF_TOKEN not found in Secrets. Please set it in Space settings.")
 print(f"HF_TOKEN loaded: {len(HF_TOKEN) if HF_TOKEN else 0} characters")
 
-# 尝试初始化 Hugging Face API 客户端
-client = None
 try:
     client = InferenceClient(model="facebook/mbart-large-50", token=HF_TOKEN)
-    response = client.get_model_info()
-    if not response:
-        raise ConnectionError("无法连接到 Hugging Face API")
-    print("Hugging Face API 连接成功")
-except Exception as e:
-    print(f"Hugging Face API 初始化失败，错误: {e}，将使用本地推理。")
-
-# 本地推理备用方案
-def local_generate_summary(text):
-    model_name = "facebook/mbart-large-50"
-    tokenizer = MBartTokenizer.from_pretrained(model_name)
-    model = MBartForConditionalGeneration.from_pretrained(model_name)
-    
-    inputs = tokenizer(text, return_tensors="pt", max_length=1024, truncation=True)
-    summary_ids = model.generate(inputs.input_ids, max_length=200, min_length=50)
-    return tokenizer.decode(summary_ids[0], skip_special_tokens=True)
-
-def generate_summary(text):
-    if client:
+    def generate_summary(text):
         for _ in range(3):
             try:
                 response = client.summarization(text)
@@ -42,21 +21,26 @@ def generate_summary(text):
                 error_details = traceback.format_exc()
                 print(f"尝试失败，错误类型: {type(e).__name__}, 错误详情: {str(e)}, 堆栈: {error_details}")
                 time.sleep(1)
-        print("API 不可用，切换到本地推理。")
-    
-    # 如果 API 不可用，使用本地推理
-    return local_generate_summary(text)
-
-interface = gr.Interface(
-    fn=generate_summary,
-    inputs=gr.Textbox(lines=5, placeholder="输入文档内容..."),
-    outputs="text",
-    title="MySmartSummary",
-    description="在线智能文档摘要工具，支持中文",
-    examples=[
-        ["今天我们讨论了2025年的项目计划，包括产品发布、市场推广和预算分配。"]
-    ],
-    css="body {background-color: #f0f0f0; font-family: Arial;}"
-)
-
-interface.launch()
+        return "网络错误，请稍后重试。"
+    interface = gr.Interface(
+        fn=generate_summary,
+        inputs=gr.Textbox(lines=5, placeholder="输入文档内容..."),
+        outputs="text",
+        title="MySmartSummary",
+        description="在线智能文档摘要工具，支持中文",
+        examples=[
+            ["今天我们讨论了2025年的项目计划，包括产品发布、市场推广和预算分配。"]
+        ],
+        css="body {background-color: #f0f0f0; font-family: Arial;}"
+    )
+except Exception as e:
+    error_details = traceback.format_exc()
+    print(f"初始化错误，错误类型: {type(e).__name__}, 错误详情: {str(e)}, 堆栈: {error_details}")
+    interface = gr.Interface(
+        fn=lambda x: f"服务暂不可用，错误: {str(e)}",
+        inputs="text",
+        outputs="text",
+        title="MySmartSummary",
+        description="服务初始化失败"
+    )
+interface.launch()